02. July 2013 · Comments Off · Categories: Uncategorized

team-on-dockThe Barrett group works on medical genomics research at the Wellcome Trust Sanger Institute. We are interested in how genetic variation affects risk for diseases, and in finding ways to apply that knowledge to improve health care. We analyze both genome-wide association studies and next-generation sequence data collected on thousands of individuals, develop statistical and computational methods for these analyses, and integrate genomics with medical practice.

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06. August 2014 · Comments Off · Categories: Conferences, Science · Tags: , ,

1000 Genomes and Beyond Conference held on 24-26 of June 2014 in Cambridge, UK was the latest of the 1000 Genome Project community meetings, marking the end of this grandiose endeavor launched in 2008. With the final Phase 3 of the 1000 Genome project being released on 24th of June, this was an excellent opportunity to get an update on this release but also to see what was learned leveraging the genetic variation catalogued in 1000 Genomes so far and provide a glimpse of future opportunities and directions.

The final, phase 3 is a catalog of genetic variants identified through low-coverage (8x) whole-genome, exome sequencing and genotyping arrays in 2,504 individuals from 26 populations (each population is represented with 60-100 individuals). The catalog includes over 79 million variant sites, covering short variants (bi- and multiallelic SNPs, indels), tandem repeats and structural variants; and is expected to contain over 95% of common variants.

1000 Genome Project had a tremendous impact on our understanding of population genetics and human evolution. It also enabled studies on population isolates, easy and effective study design which revealed a numerous candidate loci for complex traits. One of the most well-rounded studies presented during the meeting was the one about the common Greenlandic stop-gain variant in TBC1D4 conferring muscle insulin resistance and T2D. In the discovery analysis variant was found to be associated with higher plasma glucose and serum insulin levels in the Greenlandic participants without previous known T2D, while the consequent T2D case-control analysis showed strong association with increased T2D risk. The variant has a MAF of 17% in Greenlandic cohort, and it has been observed in only one Japanese individual out of all individuals sequenced in the 1000 Genome and several related large sequencing projects. The observed effect sizes are several times larger than any previous finding in large-scale GWASs of these traits, with ~60% of the homozygous carriers developing T2D between 40 and 60 years of age; indicating a Mendelian-disease-like pattern of inheritance. The well thought-out design of this study was commended, and it sparked some discussion about the often lack of population-based control groups in the studies of the extreme and rare phenotypes, where the initial ascertainment bias is introducing an upward bias in reported effect sizes.

What I found particularly encouraging is that the focus of the genetic studies is slowly moving toward the large-scale functional and mechanistic studies. This direction has been advocated for years but finally the results are being produced. From study of genetic variation in human DNA replication timing (rtQTL), high-quality and resolution transcriptome analysis, investigation of loss-of-function variants effects on transcriptome to development of new software tools for analysing sequenced variants, such as Ensembl’s variant effect predictor (VEP); are all gradually unveiling the functional consequences of genetic variation in humans. Still, some of this work is still in its infancy and will require larger, better powered studies to produce meaningful conclusions. This was nicely demonstrated during Andrew Wood’s talk on epistatic effects of genetic variants influencing gene expression levels. They sought to replicate findings from the first study reporting 30 epistasis interactions affecting traits (Hemani et al., Nature 2014) using genotypes imputed from the 1000 Genomes reference panel. 14 interaction effects were replicated, however, in each case, a third variant uncaptured in the initial study could provide explanation for the apparent epistasis. A second study reporting epistatic effects was also published in 2014 but despite the fact that sharing data between these groups helped, Wood concluded that clear picture of epistatic interaction effects on gene expression will require large samples sizes and whole-genome-sequencing.

The overall conclusion of the meeting was that developments in the computational biology methods will be of critical importance, and that data sharing and functional characterization will be the biggest challenges in human genetics in the future. Richard Durbin also noted that we should be considering the 1 Million Genomes Project, but that new initiative, goals and leadership is needed.

This year’s Biology of Genomes (BoG) meeting maintained its high standard with another display of excellent and exciting science. One of my favourite presentations was given by Matthew Stephens from the University of Chicago on the topic of False Discovery Rates (FDRs).

The FDR is a basic concept in statistical testing that we all come across in our research. By controlling the FDR, we aim to limit the expected proportion of false positives among significant loci identified by association studies. Slide1 The idea is that under the null hypothesis (H0, that the locus is not associated with the trait), the observed p-values are expected to be distributed uniformly (Fig.1(a)); and under an alternative hypothesis (H1), more of the p-values should be close to zero (Fig.1(b)). In other words, the observed distributions of p-values in a genome-wide scan should be a mixture of these two distributions. The existing FDR methods find a maximum cutoff value (Fig. 1(c)) such that the results with smaller p-values are likely to be true positives from H1.

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11. April 2014 · Comments Off · Categories: Jobs

We’re currently advertising for two positions in the lab:

  1. A postdoc to work on genomic data analysis in inflammatory bowel disease, shared with Carl Anderson’s team
  2. A software developer to help build the tools the community needs for large-scale genomic analysis more generally, and to support the variety of projects happening in the team.

The first ad closes in just a few days, so apply soon if you’re interested (the second one is open for another couple of weeks).

10. February 2014 · Comments Off · Categories: Conferences, Science · Tags: , ,

Wendy offers a retrospective on the forward-looking atmosphere at last year’s American Society of Human Genetics meeting, in Boston

Looking into the future is something I felt the Annual ASHG conference focused on more this year than last year. One man who certainly has form for looking into the future is the Dermatologist Rudolf Happle. In the eighties Happle predicted a number of genetic conditions would be mosaic and, following the advent of whole exome sequencing, he has turned out to be correct in his predictions so far. Therefore I was rather pleased to catch him as the opening speaker in a stimulating session on mosaicism chaired by Leslie Besecker and William Dobyns.
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28. October 2013 · Comments Off · Categories: Conferences, Science · Tags: , , ,

One of my favorite presentations at ASHG this year was a poster given by Brendan Bulik-Sullivan from the Broad. Brendan and his colleagues attempted to answer a puzzling question which has come up quite often recently: “If we see an inflation of GWAS test statistics, is it because of polygenic risk (good) or population stratification (bad)?”
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Recently I had my DNA genotyped by 23andMe. After working at Sanger for two years, I had been looking forward to finding out what my own genome had to say about myself, particularly regarding my ancestry. I am from Beijing and both of my parents are ethnically Han Chinese – the largest ethnic group which accounts for 92% population in China. Having witnessed my colleagues’ surprise at finding French, Ashkenazi and Scandinavian ancestry in their own DNA data, I could not help but get my hopes up to discover some surprising elements in my own ATGCs.

23andmeHowever, 23andMe left me feeling a little underwhelmed. Its ancestry analysis told me I’m 99.4% East Asian and Native American, a little like finding out that beef is 99.4% cow (something you can not always take from granted in the UK). Compared with the detailed breakdown you receive if you are European, such a vague composition is rather disappointing. Luckily, with a bit of experience in analysing genotype data, I could try other means. I combined my genotype with the east Asian cohort from our Inflammatory Bowel Disease (IBD) studies, and did a standard Principal Component Analysis (PCA) using WDIST, an experimental rewrite of the PLINK command-line tool which benefits from a vastly improved speed-up of the Identity-by-descent (—genome) calculation.

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This is a guest post by Mari Niemi, an MSc student visiting the lab this year.

DSC_0283_cleaned_smallIn the last few years, a major focus of the group has been identifying the genomic regions associated with risk of inflammatory bowel disease (IBD). Currently, there are 163 loci associated with the condition; the largest number of associations for a complex disease to date, explaining 13.6% Crohn’s disease and 7.5% ulcerative colitis total disease variance. These lists of associated loci are drawn up with some heavy-duty statistical computing, but still leave key questions about which genes in those regions are actually responsible for susceptibility to IBD – and what their role is in this complex plot? In order to understand more about the disease we need to functionally annotate these IBD candidate genes, and to do so we need to get our hands (quite literally) dirty in a laboratory!
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29. April 2013 · Comments Off · Categories: Uncategorized · Tags: , , , , , , ,

Lichfield Cathedral
On the weekend of 22nd of March, we went on our annual team retreat to Waterhouses, a village in the south of the Staffordshire Peak District. We set off from Oxford following a symposium at the Wellcome Trust Center of Human Genetics. Along the way we stopped in Lichfield to visit the famous Cathedral and the house of Erasmus Darwin (grandfather of Charles Darwin, www.erasmusdarwin.org). Surprisingly, Erasmus Darwin’s work hinted at the possibility of evolution, and although they had never met, Charles’ inspiration could have potentially come from his grandfather. We also had a nice meal in the Damn Fine Café, which had a selection of food and drink perfect for a cold winter’s afternoon.

We were really fortunate not to have lingered too long in Lichfield, as a large snowstorm rapidly descended upon the region. More »

One of the main research focuses of the Barrett group is to understand genetic associations with Inflammatory Bowel Disease (IBD), in particular with its two most common subtypes, Crohn’s disease and ulcerative colitis (UC).

Back in November 2012, in preparation for the ASHG meeting, I did a brief literature review on the development of IBD based on a number of selected publications. The motion chart below (created in R as used in the well-known Hans Rosling TED talk) shows an overview of the discovery of IBD disease loci since 2001, when three independent groups identified a CD risk gene on chromosome 16q12, NOD2, using linkage techniques.

MotionChartID17b62b2346c5
Plot: IBD Motion Chart
R version 2.15.2 (2012-10-26) • googleVis-0.2.17Google Terms of UseData Policy

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